A statistic package for python with enphasis on timeseries analysis. Built around numpy_, it provides several back-end timeseries classes including R-based objects via rpy2_. It is shipped with a domain specific language for timeseries analysis and manipulation built on to of ply_.

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.. contents:: :local:

Timeseries

To create a timeseries object directly::

>>> from dynts import timeseries
>>> ts = timeseries('test')
>>> ts.type
'numpy'
>>> ts.name
'test'
>>> ts
TimeSeries:numpy:test
>>> str(ts)
'test'

DSL

The package comes with a Domain-Specific-Language (DSL_) dedicated to timeserie analysis and manipulation. This is a simple multiplication::

>>> from dynts import api
>>> e = api.parse('2*GOOG')
>>> e
2.0 * goog
>>> len(e)
2
>>> list(e)
[2.0, goog]
>>> ts = api.evaluate(e).unwind()
>>> ts
TimeSeries:numpy:2.0 * goog
>>> len(ts)
251

Requirements

There are few requirements that must be met:

• python_ 2.6 up to python 3.3.
• numpy_ version 1.5.1 or higher for arrays and matrices.
• ply_ version 3.3 or higher, the building block of the DSL_.
• ccy_ for date and currency manipulation.

R backend

Depending on the back-end used, additional dependencies need to be met. For example, there are back-ends depending on the following R packages:

• rpy2_ if an R_ TimeSeries back-end is used (default).
• zoo_ and PerformanceAnlytics_ for the zoo back-end (currently the default one)
• timeSeries_ for the rmetrics back-end

Installing rpy2_ on Linux is straightforward, on windows it requires the python for windows__ extension library.

Optional Requirements

• cython_ for performance. The library is not strictly dependent on cython, however its usage is highly recommended. If available several python modules will be replaced by more efficient compiled C code.
• xlwt_ to create spreadsheet from timeseries.
• matplotlib_ for plotting.
• djpcms_ for the web.views module.

__ http://sourceforge.net/projects/pywin32/files/

.. _running-tests:

Running Tests

There are three types of tests available:

• regression for unit and regression tests.
• profile for analysing performance of different backends and impact of cython_.
• bench same as profile but geared towards speed rather than profiling.

From the distribution directory type::

python setup.py test

This will run by default the regression tests. To run a profile test type::

python runtests.py -t profile <test-name>

where <test-name> is the name of a profile test. To obtain a list of available tests for each test type, run::

python setup.py test -l

for unit tests, or::

python runtests.py -t profile --list

for profile, or::

python runtests.py -t bench --list

from benchmarks.

It is needed since during tests some data is fetched from google finance.

To access coverage of tests you need to install the coverage_ package and run the tests using::

coverage run runtests.py

and to check out the coverage report::

coverage report -m

.. |pypiversion| image:: https://badge.fury.io/py/dynts.svg :target: https://pypi.python.org/pypi/dynts .. |pyversions| image:: https://img.shields.io/pypi/pyversions/dynts.svg :target: https://pypi.python.org/pypi/dynts .. |license| image:: https://img.shields.io/pypi/l/dynts.svg :target: https://pypi.python.org/pypi/dynts .. |status| image:: https://img.shields.io/pypi/status/dynts.svg :target: https://pypi.python.org/pypi/dynts .. |master-build| image:: https://travis-ci.org/quantmind/dynts.svg?branch=master :target: https://travis-ci.org/quantmind/dynts .. |coverage-master| image:: https://coveralls.io/repos/github/quantmind/dynts/badge.svg?branch=master :target: https://coveralls.io/github/quantmind/dynts?branch=master .. _numpy: http://numpy.scipy.org/ .. _ply: http://www.dabeaz.com/ply/ .. _rpy2: http://rpy.sourceforge.net/rpy2.html .. _DSL: http://en.wikipedia.org/wiki/Domain-specific_language .. _R: http://www.r-project.org/ .. _ccy: http://code.google.com/p/ccy/ .. _zoo: http://cran.r-project.org/web/packages/zoo/index.html .. _PerformanceAnlytics: http://cran.r-project.org/web/packages/PerformanceAnalytics/index.html .. _timeSeries: http://cran.r-project.org/web/packages/timeSeries/index.html .. _Python: http://www.python.org/ .. _xlwt: http://pypi.python.org/pypi/xlwt .. _matplotlib: http://matplotlib.sourceforge.net/ .. _djpcms: http://djpcms.com .. _coverage: http://nedbatchelder.com/code/coverage/ .. _cython: http://www.cython.org/ .. _flot: http://code.google.com/p/flot/ .. _Sparklines: http://www.omnipotent.net/jquery.sparkline/